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Development of a geospatial model to quantify, describe and map urban growth

城市蔓延 地理空间分析 土地覆盖 填充 地理 土地利用 城市规划 地理信息学 卫星图像 遥感 地图学 环境资源管理 地理信息系统 专题制图器 计算机科学 环境规划 区域科学 环境科学 土木工程 工程类
作者
Emily H. Wilson,James D. Hurd,Daniel L. Civco,Michael P. Prisloe,Chester Arnold
出处
期刊:Remote Sensing of Environment [Elsevier]
卷期号:86 (3): 275-285 被引量:395
标识
DOI:10.1016/s0034-4257(03)00074-9
摘要

In the United States, there is widespread concern about understanding and curbing urban sprawl, which has been cited for its negative impacts on natural resources, economic health, and community character. There is not, however, a universally accepted definition of urban sprawl. It has been described using quantitative measures, qualitative terms, attitudinal explanations, and landscape patterns. To help local, regional and state land use planners better understand and address the issues attributed to sprawl, researchers at NASA's Northeast Regional Earth Science Applications Center (RESAC) at The University of Connecticut have developed an urban growth model. The model, which is based on land cover derived from remotely sensed satellite imagery, determines the geographic extent, patterns, and classes of urban growth over time. Input data to the urban growth model consist of two dates of satellite-derived land cover data that are converted, based on user-defined reclassification options, to just three classes: developed, non-developed, and water. The model identifies three classes of undeveloped land as well as developed land for both dates based on neighborhood information. These two images are used to create a change map that provides more detail than a traditional change analysis by utilizing the classes of non-developed land and including contextual information. The change map becomes the input for the urban growth analysis where five classes of growth are identified: infill, expansion, isolated, linear branch, and clustered branch. The output urban growth map is a powerful visual and quantitative assessment of the kinds of urban growth that have occurred across a landscape. Urban growth further can be characterized using a temporal sequence of urban growth maps to illustrate urban growth dynamics. Beyond analysis, the ability of remote sensing-based information to show changes to a community's landscape, at different geographic scales and over time, is a new and unique resource for local land use decision makers as they plan the future of their communities.
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